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MyJournals.org - Science - '[ASAP] Heterogeneous and Photosensitized Oxidative Degradation Kinetics of the Plastic Additive Bisphenolâ€`A in Sea Spray Aerosol Mimics' (Journal of Physical Chemistry A)

MyJournals.org - Science - '[ASAP] Heterogeneous and Photosensitized Oxidative Degradation Kinetics of the Plastic Additive Bisphenolâ€`A in Sea Spray Aerosol Mimics' (Journal of Physical Chemistry A)
myjournals.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from myjournals.org Daily Mail and Mail on Sunday newspapers.

Photosensitized Oxidative Degradation Kinetics , Plastic Additive Bisphenol , Sea Spray Aerosol Mimics , Physical Chemistry , Bundle Analysis , Electric Field Induced Changes , Electron Charge Density , Dissociative Electron Attachment ,

MyJournals.org - Science - 'Remote Sensing, Vol. 15, Pages 2618: Source Model of the 2023 Turkey Earthquake Sequence Imaged by Sentinel-1 and GPS Measurements: Implications for Heterogeneous Fault Behavior along the East Anatolian Fault Zone' (Remote Sensing)

MyJournals.org - Science - Remote Sensing, Vol. 15, Pages 2618: Source Model of the 2023 Turkey Earthquake Sequence Imaged by Sentinel-1 and GPS Measurements: Implications for Heterogeneous Fault Behavior along the East Anatolian Fault Zone (Remote Sensing) ....

East Anatolian Fault Zone , Sentinel 1 ,

Optimising Heterogeneous Catalysis Reactions

Uniqsis is at the forefront of flow reactor design, offering the cutting-edge FlowSyn™ system that sets the standard for automated optimisation of heterogeneous catalysis reactions. Click to read more. ....

"Distributional Knowledge Transfer for Heterogeneous Federated Learning" by Huan Wang, Lijuan Wang et al.

Federated learning (FL) produces an effective global model by aggregating multiple client weights trained on their private data. However, it is common that the data are not independently and identically distributed (non-IID) across different clients, which greatly degrades the performance of the global model. We observe that existing FL approaches mostly ignore the distribution information of client-side private data. Actually, the distribution information is a kind of structured knowledge about the data itself, and it also represents the mutual clustering relations of data examples. In this work, we propose a novel approach, namely Federated Distribution Knowledge Transfer (FedDKT), that alleviates heterogeneous FL by extracting and transferring the distribution knowledge from diverse data. Specifically, the server learns a lightweight generator to generate data and broadcasts it to the sampled clients, FedDKT decouples the feature representations of the generated data and transfers t ....

Federated Distribution Knowledge Transfer , Distribution Knowledge , Federated Learning , Don Iid ,